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--- |
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tags: |
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- autotrain |
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- stable-diffusion |
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- stable-diffusion-diffusers |
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- text-to-image |
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- diffusers |
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- lora |
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- template:sd-lora |
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base_model: stablediffusionapi/dreamshaperv8 |
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instance_prompt: photo of sruthi |
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license: openrail++ |
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--- |
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# ModelsLab LoRA DreamBooth Training - stablediffusionapi/my-stablediffusion-lora-4303 |
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These are LoRA adaption weights for stablediffusionapi/dreamshaperv8. The weights were trained on photo of sruthi using [ModelsLab](https://modelslab.com). |
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LoRA for the text encoder was enabled: False. |
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## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) |
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```py |
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!pip install -q transformers accelerate peft diffusers |
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from diffusers import DiffusionPipeline |
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import torch |
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pipe_id = "Lykon/DreamShaper" |
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pipe = DiffusionPipeline.from_pretrained(pipe_id, torch_dtype=torch.float16).to("cuda") |
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pipe.load_lora_weights("stablediffusionapi/my-stablediffusion-lora-4303", weight_name="pytorch_lora_weights.safetensors", adapter_name="abc") |
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prompt = "abc of a hacker with a hoodie" |
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lora_scale = 0.9 |
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image = pipe( |
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prompt, |
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num_inference_steps=30, |
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cross_attention_kwargs={"scale": 0.9}, |
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generator=torch.manual_seed(0) |
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).images[0] |
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image |
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``` |
